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double_edge_swap(G, nswap=1, max_tries=100, seed=None)

A double-edge swap removes two randomly chosen edges u-v and x-y and creates the new edges u-x and v-y:

u--v            u  v
       becomes  |  |
x--y            x  y

If either the edge u-x or v-y already exist no swap is performed and another attempt is made to find a suitable edge pair.

Notes

Does not enforce any connectivity constraints.

The graph G is modified in place.

Parameters

G : graph

An undirected graph

nswap : integer (optional, default=1)

Number of double-edge swaps to perform

max_tries : integer (optional)

Maximum number of attempts to swap edges

seed : integer, random_state, or None (default)

Indicator of random number generation state. See Randomness<randomness> .

Returns

G : graph

The graph after double edge swaps.

Swap two edges in the graph while keeping the node degrees fixed.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /networkx/algorithms/swap.py#12
type: <class 'function'>
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